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ABMUS2022: Agent-Based Modelling of Urban Systems 2022


ABMUS is a workshop where urban and geo-spatial models get together in a focused session, during the International Conference on Autonomous Agents and Multiagent Systems (AAMAS). The ABMUS2022 workshop on Agent-Based Modelling of Urban Systems will be held online on 9 or 10 May 2022 as part of the AAMAS2022 conference.

The central goal of this workshop is to bring together the community of researchers and practitioners who use agent-based models and multi-agent systems to understand and manage cities and urban infrastructure systems. Through the exchange of ideas and state-of-the-art within this area, we will pool together current thinking to discuss avenues of fruitful research and methodological challenges we face in building robust, realistic, and trusted models of urban systems. Drawing from recognised challenges faced by the modeling community through the COVID-19 pandemic and similar public policy crises, the overarching theme for the workshop this year will be ‘Trust, Transparency and Translation’. Participants will be asked to describe how their models are creating a bridge between the synthetic and real worlds, and making their way into real-world policy and decision-making. This year, we invite presentations that describe how researchers construct their models, demonstrate results, work with policy and decision-makers, and how these processes either facilitate or hinder the process of urban systems model building from the modellers perspective. We will discuss challenges associated with model development, data interoperability, consistent representation of space and time, as well as developments in interfaces and stakeholder engagement.

We invite submissions from researchers and practitioners who use agent-based models and agent systems to understand, explore, and manage cities and urban infrastructure systems. The overarching theme for 2022 is Trust, Transparency and Translation. Participants will be asked to describe how their models are creating a bridge between the synthetic and real worlds, and making their way into real-world policy and decision-making.

Discussion

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